In silico screening of protein-binding peptides with an application to developing peptide inhibitors against antibiotic resistance

Xianjin Xu; Wei-Ling Kao; Allison Wang; Hsin-Jou Lee; Rui Duan; Hannah Holmes; Fabio Gallazzi; Juan Ji; Hongmin Sun; Xiao Heng; Xiaoqin Zou

doi:10.1093/pnasnexus/pgae541

In silico screening of protein-binding peptides with an application to developing peptide inhibitors against antibiotic resistance

PNAS Nexus. 2024 Nov 27;3(12):pgae541. doi: 10.1093/pnasnexus/pgae541. eCollection 2024 Dec.

Authors

Xianjin Xu^{1

2

3

4}, Wei-Ling Kao^{2

5

6}, Allison Wang^{2

5

6}, Hsin-Jou Lee^{2

5

6}, Rui Duan^{1

2

3

4}, Hannah Holmes², Fabio Gallazzi^{7

8}, Juan Ji², Hongmin Sun⁵, Xiao Heng², Xiaoqin Zou^{1

2

3

4}

Affiliations

¹ Department of Physics, University of Missouri, Columbia, MO 65211, USA.
² Department of Biochemistry, University of Missouri, Columbia, MO 65211, USA.
³ Dalton Cardiovascular Research Center, University of Missouri, Columbia, MO 65211, USA.
⁴ Institute of Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA.
⁵ Department of Medicine, University of Missouri, Columbia, MO 65211, USA.
⁶ Department of Pharmacology, National Yang Ming Chiao Tung University College of Medicine, Taipei 112304, Taiwan.
⁷ Molecular Interactions Core, University of Missouri, Columbia, MO 65211, USA.
⁸ Department of Chemistry, University of Missouri, Columbia, MO 65211, USA.

Abstract

The field of therapeutic peptides is experiencing a surge, fueled by their advantageous features. These include predictable metabolism, enhanced safety profile, high selectivity, and reduced off-target effects compared with small-molecule drugs. Despite progress in addressing limitations associated with peptide drugs, a significant bottleneck remains: the absence of a large-scale in silico screening method for a given protein target structure. Such methods have proven invaluable in accelerating small-molecule drug discovery. The high flexibility of peptide structures and the large diversity of peptide sequences greatly hinder the development of urgently needed computational methods. Here, we report a method called MDockPeP2_VS to address these challenges. It integrates molecular docking with structural conservation between protein folding and protein-peptide binding. Briefly, we discovered that when the interfacial residues are conserved, a sequence fragment derived from a monomeric protein exhibits a high propensity to bind a target protein with a similar conformation. This valuable insight significantly reduces the search space for peptide conformations, resulting in a substantial reduction in computational time and making in silico peptide screening practical. We applied MDockPeP2_VS to develop peptide inhibitors targeting the TEM-1 β-lactamase of Escherichia coli, a key mechanism behind antibiotic resistance in gram-negative bacteria. Among the top 10 peptides selected from in silico screening, TF7 (KTYLAQAAATG) showed significant inhibition of β-lactamase activity with a K _i value of 1.37 ± 0.37 µM. This fully automated, large-scale structure-based in silico peptide screening software is available for free download at https://zougrouptoolkit.missouri.edu/mdockpep2_vs/download.html.

Keywords: antibiotic resistance; in silico peptide screening; molecular docking; peptide drug discovery; protein–peptide interactions.